Method and System for Implementing Navigation Using Bounded Geograhic Regions

1. A method of implementing navigation guidance using Bounded Geographic Regions (“BGR”), containing, at a minimum, an end-user device with means for inputting destinations and receiving routing guidance; a map database, containing roads and, optionally, points of interest (“POIs”); a Global Positioning System (“GPS”) receiver determining vehicle position; an assemblage of memory and processing elements referred to as a server; a means for communicating between the end-user device and the server; a Node Pair Look-up Table (“NPLUT”) database which is initially, either partially or fully, loaded with explicit solutions for the dependent variable for each Node Pair, and which contains explicit solutions between each potential entry node and each potential exit node of every BGR of interest to the end user, each BGR being an area bounded by a defined perimeter, wherein no BGRs overlap, and all areas of interest to the end user are included in a BGR; and wherein a node is the point at which a road segment intersects with a defined perimeter of a BGR; and a navigation software core, resident on the server, having the capability to create BGRs of such a size that explicit navigation solutions are possible within the boundaries of the BGR, to identify Node Pairs for each BGR which might be part of a potential solution, and to optimize a navigation solution based on the dependent variable provided by the user, said dependent variable being at least one of distance, time, fuel, or user-defined cost-function, and the independent variables which are inherently part of a solution database, said independent variables being at least a plurality of day of week, date, time of day, a unique driver identifier, and unique vehicle identifier; wherein BGRs are generated in the map database by first performing, on the server, at least one of projecting equidistant latitude lines across all said map database areas of interest, and identifying a plurality of corners of each said BGR.

2. The method of implementing navigation guidance using BGRs in claim 1 , in which the BGRs are categorized as either degenerate or regular, with degenerate BGRs being defined as ones with either only a single node or no node, and regular BGRs being defined as ones with two or more nodes.

3. The method of implementing navigation guidance using BGRs in claim 2 , in which the generation of BGRs is performed so as to minimize variance in the surface area of regular BGRs, by allowing degenerate BGRs to have varying areas, aspect ratios, sides, and shapes.

4. The method of implementing navigation guidance using BGRs in claim 3 , in which generation of BGRs is performed separately for each of a plurality of areas of interest, with the BGRs for the plurality of said areas of interest being knitted or stitched together.

5. The method of implementing navigation guidance using BGRs in claim 4 , in which said knitting or stitching together of the plurality of said areas of interest is performed through the use of degenerate BGRs.

6. The method of implementing navigation guidance using BGRs in claim 3 , in which BGR generation is started along a shoreline of any body of water.

7. The method of implementing navigation guidance using BGRs in claim 6 , in which said body of water is a pond, reservoir, lake, or sea that covers an area at least four (4) or more times the average area of the regular BGRs in the area of interest.

8. The method of implementing navigation guidance using BGRs in claim 1 , in which frames edges, drawn by using lines, splines, curves, and polygons, connect said corners of said BGRs.

9. The method of implementing navigation guidance using BGRs in claim 8 , in which BGRs are generated, using an Exclusionary Distance, said Exclusionary Distance being a linear distance that said BGR frame edges are from all traffic control devices and intersections.

10. The method of implementing navigation guidance using BGRs in claim 1 , in which each BGR is identified by a unique alphanumeric, decimal, binary, or hexadecimal representation.

11. The method of implementing navigation guidance using BGRs in claim 10 , in which each node is identified by a unique alphanumeric, decimal, binary, or hexadecimal representation.

12. The method of implementing navigation guidance using BGRs in claim 11 , in which said unique representations of said nodes include a designator identifying the BGRs that said node touches.

13. The method of implementing navigation guidance using BGRs in claim 1 , in which each node is stored as a linked list, with a pointer identifying each BGR which said node contacts.

14. The method of implementing navigation guidance using BGRs in claim 1 , in which Super BGRs, composed of a plurality of BGRs, are used to track peculiar local traffic laws, driver customs, and other localized behavior that affect traffic flow.

15. The method of implementing navigation guidance using BGRs in claim 1 , in which historical, time-dependent behavior of traffic within each said BGR, including traffic density, average speed, and instantaneous speed as a function of location between two nodes, is used to perform data analysis.

16. The method of implementing navigation guidance using BGRs in claim 15 , in which said data analysis of historical, time-dependent behavior of traffic is used to predict future traffic patterns.

17. The method of implementing navigation guidance using BGRs in claim 16 , in which the future traffic patterns relate to a special event or function, at which a large crowd of people gather.

18. The method of implementing navigation guidance using BGRs in claim 15 , in which traffic within each said BGR is modeled as a longitudinal wave, creating within each said BGR an eigenmode with a 24 hour cycle.

19. The method of implementing navigation guidance using BGRs in claim 18 , in which said traffic within each said BGR has a time-dependent impedance, resonance, and Quality factor.

20. The in claim 1 , in which the average area of the BGRs is minimized to no more than 1000 sq. ft.

21. The method of implementing navigation guidance using BGRs in claim 20 , in which traffic within each said BGR is modeled as a longitudinal wave, creating within each said BGR an eigenmode with a 24 hour cycle.

22. The method of implementing navigation guidance using BGRs in claim 21 , in which the traffic within each said BGR has a time-dependent impedance, resonance, and Quality factor.

23. The method of implementing navigation guidance using BGRs in claim 1 , in which the average area of the BGRs is minimized to a single pixel.

24. A system of implementing navigation guidance using BGRs, containing, at a minimum, an end-user device with means for inputting destinations and receiving routing guidance; a map database, containing roads and, optionally, points of interest (“POIs”); a GPS receiver; a server; a means for communicating between the end-user device and the server; a Node Pair Look-up Table (“NPLUT”) database which is initially, either partially or fully, loaded with explicit solutions for the dependent variable for each Node Pair, and which contains explicit solutions between each potential entry node and each potential exit node of every BGR of interest to the end user, each BGR being an area bounded by a defined perimeter, wherein no BGRs overlap, and all areas of interest to the end user are included in a BGR; and wherein a node is the point at which a road segment intersects with a defined perimeter of a BGR; and a navigation software core, resident on the server as non-transitory computer readable code, having the capability to create BGRs of such a size that explicit navigation solutions are possible within the boundaries of the BGR, to identify Node Pairs for each BGR which might be part of a potential solution, and to optimize a navigation solution based on the dependent variable provided by the user, said dependent variable being at least one of distance, time, fuel, or user-defined cost-function, and the independent variables which are inherently part of a solution database, said independent variables being at least a plurality of day of week, date, time of day, a unique driver identifier, and unique vehicle identifier; wherein BGRs are generated in the map database by first performing, on the server, at least one of projecting equidistant latitude lines across all said map database areas of interest, and identifying a plurality of corners of each said BGR.